Present day data processing systems are often configured in large multi-user networks. Management of such networks may typically include the need to transfer large amounts data to an endpoint system from a source system (or, simply, “a source”) and the collection of information, for example, error reports from a multiplicity of endpoints systems (or, simply, “endpoints”).
Such large data transfers may occur within a network, for example, to distribute software updates. The system administrator may need to allocate a specific period of time for the bulk data transfer to more efficiently utilize network resources. This may typically occur when the communication load on the system is lowest, usually at night when most endpoint users are not working at their stations. The system administrator may load the bulk data and the corresponding transfer instructions onto the network system's source, or server, in preparation for the transfer. At the predetermined time set by the administrator, the server will push the data while ensuring that the bulk data is successfully transferred to each of the desired endpoint locations. However, during the transfer a portion of the system server is dedicated to the data transfer and thus unavailable for other networking tasks. Moreover, as the number of endpoints which must be simultaneously serviced by the bulk data distribution increases, network bandwidth demands are concomitantly increased. This complicates scalability of the bulk distribution systems.
Therefore, a need exists in the art for a bulk distribution mechanism that can transfer large amounts of data between network connected subsystems (or nodes) while maintaining scalability. Additionally, there is a need in such distribution mechanisms for methods and apparatus to distribute bulk data to a multiplicity of endpoints and to collect bulk data, including large log files, from the endpoints.